BRAF V600E is a determinant of sensitivity to proteasome...
Transcript of BRAF V600E is a determinant of sensitivity to proteasome...
BRAF V600E is a determinant of sensitivity to proteasome inhibitors
Davide Zecchin1,2,§*, Valentina Boscaro3*, Enzo Medico1,2, Ludovic Barault2, Miriam Martini1,2$, Sabrina Arena2, Carlotta Cancelliere2,4, Alice Bartolini2, Emily H Crowley2, Alberto Bardelli1,2,4, Margherita Gallicchio3#, Federica Di Nicolantonio1,2#
1Department of Oncology, University of Torino, 10060 Candiolo (Torino), Italy
2IRCC Institute for Cancer Research and Treatment at Candiolo, 10060 Candiolo (Torino), Italy
3Dipartimento di Scienza e Tecnologia del Farmaco, University of Torino, 10125 Torino, Italy
4FIRC Institute of Molecular Oncology (IFOM), 20139 Milano, Italy
* These authors contributed equally to this work § Present address: Signal Transduction Laboratory, Cancer Research UK London Research Institute, 44 Lincoln’s Inn Fields, London WC2A 3LY, UK $ Present address: Dipartimento di Biotecnologie Molecolari e Scienze per la Salute, Molecular Biotechnology Center, 10100 Torino, Italy
RUNNING TITLE: Proteasome inhibitors are active on BRAF mutant cells
KEYWORDS: colorectal cancer, BRAF, isogenic models, proteasome inhibitors FINANCIAL SUPPORT: The research leading to these results received funding from Fondazione Piemontese per la Ricerca sul Cancro ONLUS grant ‘Farmacogenomica – 5 per mille 2009 MIUR’ (F. Di Nicolantonio); AIRC grant MFAG 11349 (F. Di Nicolantonio); the European Community‘s Seventh Framework Programme under grant agreement n. 259015 COLTHERES; AIRC 2010 Special Program Molecular Clinical Oncology 5xMille, Project n. 9970 (A. Bardelli and E. Medico); Intramural Grants Fondazione Piemontese per la Ricerca sul Cancro ONLUS (5 per mille 2008 MIUR) to A. Bardelli, E. Medico and F. Di Nicolantonio. D. Zecchin and L. Barault are recipients of a post-doctoral fellowship from the Fondazione Umberto Veronesi – Young Investigator Programme 2013.
# Correspondence to: Margherita Gallicchio, Dipartimento di Scienza e Tecnologia del Farmaco, University of Torino, Via Pietro Giuria 9, Torino I-10125, Italy. Tel. +39-011-6707690. E-mail: [email protected]
Federica Di Nicolantonio, Department of Oncology, University of Torino, Institute for Cancer Research and Treatment at Candiolo, SP 142 Km 3.95, Candiolo, I-10060, Turin, Italy. Tel. +39-011-9933827. Fax +39-011-9933225. E-mail: [email protected]
Disclosure of Potential Conflicts of Interest: Dr A Bardelli is a shareholder and a paid member for Scientific Advisory Board at Horizon Discovery Ltd, UK, to which some of the cell lines described in this article have been licensed through the University of Turin. The other authors declare no potential conflicts of interest.
Abbreviation List: HER-2: Epidermal Growth Factor Receptor 2; EGFR: Epidermal Growth Factor Receptor; HME-1: hTERT-HME-1; CRC: Colorectal cancer; KI: Knock-in
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ABSTRACT
A critical step towards defining tailored therapy in cancer patients is the
identification of genetic interactions that may impair – or boost – the efficacy
of selected therapeutic approaches. Cell models able to recapitulate
combinations of genetic aberrations are important to find drug-genotype
interactions poorly affected by the heterogeneous genetics of human tumors.
In order to identify novel pharmacogenomic relationships, we employed an
isogenic cell panel that reconstructs cancer genetic scenarios. We screened a
library of 43 compounds in human hTERT-HME1 epithelial cells in which
PTEN or RB1 were silenced in combination with the targeted knock-in of
cancer-associated mutations in EGFR, KRAS, BRAF or PIK3CA oncogenes.
Statistical analysis and clustering algorithms were applied to display similar
drug response profiles and mutation-specific patterns of activity.
From the screen, we discovered that proteasome inhibitors show selectivity
towards BRAF V600E mutant cells, irrespective of PTEN or RB1 expression.
Preferential targeting of BRAF mutant cells by proteasome inhibitors was
corroborated in a second BRAF V600E isogenic model, as well as in a panel
of colorectal cancer cell lines by the use of the proteasome inhibitor
carfilzomib. Notably, carfilzomib also showed striking in vivo activity in a BRAF
mutant human colorectal cancer xenograft model. Vulnerability to proteasome
inhibitors is dependent on persistent BRAF signaling, since BRAF V600E
blockade by PLX4720 reversed sensitivity to carfilzomib in BRAF mutant
colorectal cancer cells.
Our findings indicated that proteasome inhibition might represent a valuable
targeting strategy in BRAF V600E mutant colorectal tumors.
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INTRODUCTION
Over the past decade, research has demonstrated that the clinical benefit
from targeted therapies is dependent upon our knowledge of the presence of
specific genetic aberrations within the tumor (1-9). To maximize therapy
efficacy, treatment must be tailored to the genetic milieu of a specific tumor, to
deliver what is referred to as ’precision medicine’.
This approach has led to progress in the treatment of specific malignancies
including breast cancers overexpressing or harboring amplified Epidermal
Growth Factor Receptor 2 (HER-2) that can be successfully treated with
trastuzumab (5). In addition, lung cancers carrying specific mutations in the
Epidermal Growth Factor Receptor (EGFR) are particularly sensitive to EGFR
tyrosine kinase inhibitors gefitinib and erlotinib (1-4). Recent examples also
include selective clinical activity of the BRAF inhibitors vemurafenib or
dabrafenib in melanomas with BRAF V600E mutation (6, 7) or the efficacy of
the ALK inhibitor crizotinib for the treatment of lung cancers carrying
translocation of the ALK kinase (8, 9).
However, only about 50% of patients with BRAF-mutant melanoma, 30% of
patients with HER2-amplified breast cancer, and 60% of patients with EGFR-
mutant or ALK-translocated lung cancer respond to blockade of the
corresponding targets (1-9). Simple binary relationships between genetic
aberrations and drug response are complicated in these cases by the intricate
genetic landscape of solid tumors (10). Indeed, in most instances, multiple
tumor suppressor mutations and oncogene variants occur in the same solid
tumor [http://cancergenome.nih.gov/] and it is thought that together these
molecular alterations contribute to patients’ response to specific anti-cancer
treatment. It has been reported, for instance, that sensitivity of EGFR mutant
lung cancer cells to EGFR tyrosine kinase inhibitors is reduced by inactivation
of PTEN (11, 12). The activation of the PI3K pathway, defined by PTEN loss
and/or PIK3CA mutation, was also associated with poor response to
trastuzumab and shorter survival time in HER-2 positive metastatic breast
cancer (13, 14). This indicates that the influence of tumor complex genetics on
therapy response warrants further consideration.
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Nevertheless, there is paucity of functional studies that systematically
evaluate the effect of complex genotypes in the modulation of drug responses.
We believe that such experimental approaches are fundamental in order to
identify novel drug-genotype interactions that are unaffected by the
concomitant presence of other common genetic alterations. On the other
hand, these studies may improve our ability to predict response to existing
anti-cancer therapies based on the plethora of genetic aberrations present in
a solid tumor.
In this report we employed a previously characterized panel of isogenic
human cell lines that recreate possible molecular scenarios observed in
human cancer (15). Using homologous recombination we introduced the
activating mutations EGFR delE746-A750, PIK3CA H1047R, PIK3CA E545K,
KRAS G13D and BRAF V600E into the genome of the non-transformed
human cell line hTERT-HME-1 (abbreviated as HME-1), which already
harbors the C176F on TP53. This TP53 mutation was previously reported to
impair the TP53 checkpoint response to genotoxic stress in HME-1 cells (15).
PTEN or RB1 tumor suppressor genes have been systematically silenced in
these isogenic cell lines generating a combinatorial model referred to as the
“matrix” (See Supplementary figure S1).
Using the HME-1 matrix, we investigated the role of single or multiple cancer
genetic alterations in modulating response to antineoplastic drugs. This
approach uncovered a novel pharmacogenetic interaction between
proteasome inhibitors and the BRAF V600E allele.
The BRAF V600E mutation occurs in 5-8% of advanced colorectal cancer
(CRC) samples. Metastatic CRC patients with BRAF mutant tumors have a
poor prognosis and do not respond to BRAF inhibitors in monotherapy (16,
17). Accordingly, the development of therapeutic strategies for metastatic
BRAF mutated CRC represent an urgent and unmet clinical need. We
therefore elected to evaluate the activity of proteasome inhibitors in BRAF
mutant colorectal cancer models. Finally, we investigated the ability of
selective BRAF targeted agents to modulate response to the proteasome
inhibitor carfilzomib in BRAF mutant colorectal cancer cells.
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MATERIALS AND METHODS
Cells and cell culture reagents
The hTERT-HME1 cell line was obtained from the American Type Culture
Collection (LGC Standards S.r.l, Milan, Italy). in October 2005, CACO2, NCI-
H716, HuTu80, COLO201, SW1417 and LS411N cell lines were purchased
from American Type Culture Collection (LGC Standards S.r.l, Milan, Italy) in
June 2010. COLO320 and HCA7 were obtained from ECACC in September
2009 (distributed by Sigma-Aldrich Srl, Milan, Italy). CaR1 and OUMS23 cell
lines were purchased from the Japanese Collection of Research Bioresources
(JCRB) (Tokyo, Japan) in January 2011. The HDC135 cell line was obtained
from the German Collection of Microorganisms and Cell Cultures (DSMZ)
repository (Braunschweig, Germany) in November 2010. The NCI-H630,
KM20 and SNU-C5 cell lines were purchased from the Korean Cell Bank
(Seoul, Korea) in February 2011. VACO432 and RKO cells were obtained
from Horizon Discovery (Cambridge, UK) in March 2011. LIM1215, LIM2405
and LIM2537 cell lines (18, 19) were provided by Prof R. Whitehead,
Vanderbilt University, Nashville, with permission from the Ludwig Institute for
Cancer Research, Melbourne branch, Australia in August 2011. The DiFi and
OXCO1 cell lines were a kind gift from Dr J. Baselga in November 2004
(Oncology Department of Vall d'Hebron University Hospital, Barcelona, Spain)
and Dr V. Cerundolo in March 2010 (Weatherall Institute of Molecular
Medicine, University of Oxford, UK), respectively. The genetic identity of the
cell lines used in this study was confirmed by STR profiling (Cell ID, Promega)
no longer than six months before drug profiling experiments. All cells were
cultured as previously described (15) or as per manufacturers’
recommendation. All cell culture media was supplemented with 10% FBS or
5% for HME-1 (Sigma–Aldrich), 50 units/ml penicillin and 50 mg/ml
streptomycin. Geneticin (G418) was purchased from Gibco and Puromycin
from Sigma-Aldrich.
Construction of isogenic models
The generation of the HME-1 matrix has been previously reported (15). All
experimental procedures for BRAF V600E targeting vector construction, AAV
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production, cell infection and screening for recombinants have been described
elsewhere (20, 21).
Drug proliferation assay
Parental and mutated cells were seeded in 100 μl complete growth medium at
a density of 3 × 103 cells/well in 96-well plastic culture plates. After serial
dilutions, 100 μl of drugs in serum-free medium were added to cells with a
multichannel pipette. Vehicle and medium-only containing wells were added
as controls. Plates were incubated at 37 °C in 5% CO2 for 96 h, after which
cell viability was assessed by ATP content using the CellTiter-Glo
Luminescent Assay (Promega). To account for clonal variability, two
independent isogenic knock-in (KI) clones infected with scramble shRNA, or
with shRNAs targeting PTEN or RB1 were tested. All luminescence
measurements (indicated as relative light units RLU) were recorded by the
Victor X4 Multilabel Plate Reader (PerkinElmer). In Supplementary Table S1
we have reported a list of tested compounds, their chemical formula, their
molecular weight (MW), the solvent used for suspension, the concentration of
stock solutions, the concentrations tested in the experiments and the storage
conditions used for the stock. Each compound was preliminary tested on
HME-1 parental cells infected with scramble shRNA to determine the
concentration referred to as the highest no-observed effect level (NOEL), the
IC50, and the IC90 values, as previously reported (20). The three
concentrations of each compound tested on the entire isogenic cell panel
were selected on these premises.
Proteasome activity assay
Proteasome activity was assayed using Proteasome-Glo™ Chymotrypsin-Like
Cell-Based Assay (Promega). Cells were seeded 16 h prior to drug treatment.
Proteasome activity was measured after 2 h incubation with proteasome
inhibitors following the manufacturer’s protocol.
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SDS PAGE and Western Blot
Cell lysates were prepared in boiled Laemmli buffer (2.5% SDS, 125mM Tris
HCl, PH 6.8). Lysates were sonicated, cleared by centrifugation at 14000 rpm
for 10 minutes at room temperature and the supernatant containing soluble
protein was removed. The protein concentration of the supernatant was
determined by micro-BCA protein assay (Pierce). An equal amount (25μg) of
whole cell lysate per lane was boiled in LDS buffer and reducing agent,
according to the manufacturers’ instructions, and separated by SDS-PAGE on
10% pre-casted polyacrylamide mini-gels (Invitrogen). The separated lysates
were then transferred to a nitrocellulose membrane. The blot was incubated
with blocking buffer (TBS-10% BSA) for 1 h at room temperature and
incubated overnight with the primary antibody (diluted according to
manufacturers’ instructions in TBS-5% BSA) at 4°C. The blot was then
washed three times for 10 min in washing buffer (TBS containing 0.2% Tween
20), incubated with secondary antibody HRP-conjugate (Sigma) (diluted
1:10,000 - 1:2,000) and washed a further three times. ECL solution
(Enhanced Chemioluminescence System, Amersham) was then added to the
filter, and the chemiluminescent signal was acquired by the LAS4000 Image
reader (Fujifilm). Antibodies used for immunoblotting were: anti-P21, anti-
PARP, anti-PTEN, and anti-RB1 (Cell Signaling Technology); anti-EGFR
(clone 13G8, Enzo Life Sciences); anti-Ubiquitin (Santa Cruz); anti–Actin
(Sigma-Aldrich).
Pharmacology data analysis (‘Pharmarray’)
Cell viability at each drug concentration was initially normalized to vehicle-
treated cells for each cell line and triplicate observations within the same
experiment were averaged. We then calculated, within each experiment, drug
response as follows: we considered the difference between the Log2 viability
of the parental cell line and the Log2 viability of a given mutant/genotype. All
drug concentrations were tested on each cell line at least three times. Drug
responses associated to a given mutant and obtained in individual
experiments were considered as distinct entities in the following clustering
analysis. Similarly, responses to different concentrations of each compound
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were analyzed as distinct elements in the clustering experiments. All data
were clustered and visualized using the publicly available GEDAS software
(22) (http://sourceforge.net/projects/gedas).
An array of data was generated in which the red color indicates higher
sensitivity (i.e. lower Log2 viability respect to the parental cell line) of a given
mutant to a specific drug concentration while the green color indicates lower
sensitivity (i.e. higher Log2 viability respect to the parental cell line).
The genotypes of the cell lines tested in individual experiments were
displayed on the horizontal axis and we performed an un-supervised, average
linkage hierarchical clustering by uncentered Pearson’s correlation coefficient.
Different drug concentrations were listed in the vertical axis and clustered by
C-means Fuzzy algorithm using an average cosine correlation coefficient. The
different clustering metrics were chosen based on the results of the clustering
optimization tool included in GEDAS.
Combination effects of PLX4720 and carfilzomib were assessed using the
method established by Poch et al. (23). We elected to employ the methods of
Poch et al. as they propose a corrective factor for dose response curves
having a slope different from 1, such as those shown by PLX4720 in most
BRAF mutant colorectal cancer cell lines. For this reason, the Poch method
results in a more accurate estimation of combination effects when the agents
show a relatively flat dose-response curve.
Statistics
Unsupervised clustering analysis was paralleled by statistical evaluation of the
genotype-specific differences of the drug responses performed by a t-test.
Specifically, the statistical test compared the responses of the different mutant
cell lines to a given compound with the response of the wild type scramble
control cells. With this aim, a heteroscedastic two-tailed t-test was employed
for all mutants as well as for all compounds (see Supplementary Table S2 for
the complete list of t-tests). In the other experiments, statistically significant
differences between groups were determined by using the heteroscedastic
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Student two-tailed t test. A value of P<0.05 was considered statistically
significant.
Xenograft studies
All animal procedures were approved by the Ethical Commission of the
Institute for Cancer Research and Treatment and by the Italian Ministry of
Health. RKO cells were injected subcutaneously into the right posterior flanks
of 7-week-old female CD-1 nude mice (6 animals per group; Charles River,
Calco, Italy). Tumor volumes were determined using [D × (d2)]/2, in which D
represents the largest diameter of the tumor, and d represents the largest
perpendicular volume to D. When tumors reached a volume of approximately
200–250 mm3, mice were randomly assigned to treatment with vehicle or
drug. For in vivo experiments, carfilzomib was formulated in an aqueous
solution of 10% (w/v) sulfobutylether-b-cyclodextrin (Captisol, a free gift from
CYDEX Pharmaceuticals, Inc, La Jolla, USA) and 10 mmol/L sodium citrate
(pH 3.5). Carfilzomib solutions were diluted daily with vehicle before tail vein
injections. Carfilzomib was administered on days 1, 2, 8, 9, 15 and 16 in 28-
day cycles at a dose of 4 mg/Kg.
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RESULTS
The isogenic “matrix” of genotypes recapitulates known interactions
between drugs and multiple genetic alterations
We initially assessed whether the HME-1 cellular matrix could recapitulate
pharmacogenomic relationships previously established experimentally and
clinically.
Previous research showed that EGFR kinase inhibitors are more effective in
cells carrying EGFR mutations but the concomitant loss of PTEN impairs this
response (11, 12).
Therefore, we focused on HME-1 isogenic cell lines knock-in (KI) for the
EGFR E746-A750 allele and on their isogenic counterpart lacking PTEN
expression. We evaluated the genotype-dependent response of these models
to EGFR tyrosine kinase inhibitors as a test case.
We observed that erlotinib, canertinib, lapatinib, classified as inhibitors of the
HER family receptor tyrosine kinase, as well as the dual EGFR – VEGFR
inhibitor vandetanib affected the growth of HME-1 isogenic cell lines in which
the EGFR E746-A750 allele was knocked in. Concomitant inactivation of
PTEN partially rescued this phenotype (Fig. 1A and 1B).
On the other hand, we observed that the KI of BRAF V600E allele conferred
resistance to EGFR inhibitors (Fig. 1A) confirming previous findings (24, 25).
These results indicate that HME-1 isogenic models harboring multiple genetic
alterations can recapitulate complex drug-genotype relationships found in
patients.
Drug screening of isogenic cell lines carrying combinations of genetic alterations
Next, we exploited the isogenic HME-1 matrix to seek novel pharmacogenetic
interactions.
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We assembled a library of 43 compounds (Supplementary Table S3),
including: i) molecules targeting tyrosine kinase receptors (RTKs) or their
effectors (e.g. anti-HERs, anti-MEK, anti-SRC, anti-AKT, anti-mTOR); ii)
compounds that do not target members of the RTK signaling pathways, but
are employed as anti-cancer therapies (PARP, proteasome, HSP90 inhibitors,
epigenetic modulators); iii) drugs in clinical use aside from cancer therapy but
that have been shown to have anti-proliferative and anti-neoplastic activity
(indomethacin, statins). Most of the drugs included in the list are approved by
the FDA/EMA or are undergoing clinical trials in cancer patients.
Each compound was tested on parental HME-1 cells and on their derivatives
infected with a scramble (non-target) shRNA to verify whether and to what
extent infection by lentivirus impacted drug response. No significant
differences in response were detected (data not shown). Furthermore, no
significant differences were also observed when we evaluated the effect of
lentiviral infection on proliferation of the KI cells carrying oncogenic mutations
in KRAS, BRAF, PIK3CA or EGFR as compared to their wild type counterpart
(Supplementary Fig. S2).
The matrix was subsequently assayed for drug responses by a proliferation
assay, using at least three drug concentrations and two clones for each
different KI genotype. All drugs were tested at least three times on each cell
line. Drug responses of mutant cells were normalized to the response of
parental scramble HME-1 as described in the methods. Normalized data was
then clustered and plotted on an array using the GEDAS software (22). This
approach was previously developed and described for the analysis of
differential drug activity in KI isogenic models and is defined as a ‘Pharmarray’
(20). Cell lines and drugs were clustered based on their response profile. The
entire analyzed dataset is shown in Supplementary Fig. S3. Magnification of a
drug cluster is shown in Fig. 2 as a relevant example. The pharmarray
analysis revealed that in most cases the genotypes sharing a KI mutation or a
knocked down tumor suppressor gene were clustered together.
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The presence of these clusters suggested that the genotype of HME-1
isogenic models strongly influenced the pattern of response of these cells to
the compounds.
BRAF mutant isogenic HME-1 cells show increased sensitivity to
proteasome inhibitors
The cluster of drugs in Fig. 2 preferentially inhibited the PIK3CA E545K,
KRAS G13D and BRAF V600E mutated genotypes. Intriguingly, this cluster of
compounds included three different concentrations of the proteasome inhibitor
bortezomib. We focused further on the effect of this compound toward BRAF
mutant cells, as this drug-genotype interaction was the most novel in our
panel and of potential translational relevance. Indeed, no influence of PTEN or
RB1 knock-down on bortezomib activity was observed in the cluster.
The preferential targeting of HME-1 BRAF KI clones by proteasome inhibitors
was confirmed using the non-boronic agent carfilzomib (Fig. 3A and 3B).
These results pointed at proteasome per se as a key molecular determinant of
the pharmacological response.
In order to elucidate the relationship between BRAF mutated cell lines and
proteasome inhibitors, we measured the amount of ubiquitinated proteins
following bortezomib treatment. We found that BRAF mutant cells
accumulated more ubiquitinated protein with respect to the wild type
counterpart (Fig. 3C). This was also observed following carfilzomib treatment
(Supplementary Fig. S4).
Treatment of HME-1 BRAF V600E with clinically relevant concentrations of
bortezomib resulted in increased p21 levels and PARP cleavage (Fig. 3C).
Proteasome inhibitors appear, therefore, to elicit a greater growth inhibitory
and apoptotic response in BRAF V600E KI cell lines likely due to an
accumulation in ubiquitinated protein.
Increased accumulation of ubiquitinated protein in BRAF KI cell lines following
treatment with proteasome inhibitors may be due to a higher basal
proteasome activity in these cells. To investigate this hypothesis, we
measured the proteasome activity in wild type versus BRAF V600E cell lines
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under basal conditions and following proteasome inhibitor treatment. To this
aim, we employed a cell-based proteasome activity assay, which determines
the chymotrypsin-like activity associated with intact proteasomes toward a
luminogenic peptide substrate. We showed that BRAF mutated HME-1 had
higher basal chymotrypsin-like activity with respect to wild type cells under
basal conditions. Bortezomib treatment reduced activity to comparable levels
in all isogenic cell lines (Fig. 3D). The greater fold inhibition of proteasome
activity correlates with the increased rate of ubiquitinylated protein
accumulation in BRAF V600E with respect to the wild type.
BRAF mutant colorectal (CRC) cells display increased sensitivity to
proteasome inhibitors
We then elected to assess the interaction between BRAF inhibitors and
response to proteasome inhibitors in CRC, a malignancy in which the BRAF
mutation confers poor prognosis in the metastatic setting. To this end we
generated a BRAF V600E isogenic cell line using LIM1215 cells, which are
wild type for KRAS, BRAF and PIK3CA (18, 26). Using a previously
developed methodology (20), we infected LIM1215 cells with a recombinant
adeno-associated viral vector carrying the BRAF V600E allele. After selection,
we isolated two independent clones in which the mutation was introduced
(knocked-in) by homologous recombination in heterozygosity under the gene’s
own promoter. Bortezomib and carfilzomib preferentially inhibited the growth
of BRAF KI clones with respect to the parental counterpart (Fig. 4A and 4B).
This confirmed that our findings in the breast cancer HME-1 matrix can also
be applied to the CRC cell line LIM1215.
Taking advantage of recent molecular profiling efforts in which the genomic
landscape of a large panel of cell lines were characterized (27, 28), we sought
to further validate this pharmacogenomic relationship using 12 CRC cell lines
harboring BRAF V600E mutations. We also selected 8 CRC cell lines wild
type for BRAF and KRAS as negative controls. We independently verified by
Sanger sequencing the mutational status of selected hotspots, including
BRAF exon 15, KRAS exons 2-3-4, NRAS exons 2-3 and PIK3CA exons 9-20.
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We observed that CRC cell lines with BRAF V600E mutations were
particularly responsive to carfilzomib, whilst wild type cells were significantly
less affected (p<0.05) (Fig. 4C). We also showed that sensitivity to carfilzomib
is independent of the PTEN or RB1 expression status in CRC cell lines (Fig.
4D).
These results confirmed that oncogenic BRAF is a novel determinant of
sensitivity to proteasome inhibitors. However, the presence of few outlier non-
responder cell lines highlighted the potential influence of additional factors,
beyond PTEN or RB1 in shaping drug response.
We have recently proposed that EGFR expression can be a determinant of
resistance to BRAF or MEK inhibitors in BRAF mutant CRC cells (29). We
asked whether EGFR expression could also be related to the lack of activity of
the proteasome inhibitor in some CRC models. However, we did not detect
any association between response to carfilzomib and EGFR expression in this
panel of cancer cells, independently from BRAF status (Fig. 4D).
Next, we sought to investigate whether the addiction of BRAF mutant cells to
proteasome function was dependent upon the activity of the BRAF V600E
mutant protein. To this aim, two BRAF-mutant CRC lines sensitive to
proteasome inhibition (SNU-C5 and LS411N) were treated with carfilzomib
and with the BRAF V600E inhibitor PLX4720, alone or in combination. Indeed,
PLX4720 co-treatment impaired the response to the proteasome inhibitor and
antagonism between these drugs was observed in both cell lines (Fig. 5).
These findings suggest that the persistent activation of BRAF V600E signaling
is required for the activity of proteasome inhibitors in BRAF mutant CRC cell
lines.
Finally, we tested the in vivo efficacy of the proteasome inhibitor carfilzomib
as single agent on BRAF mutant xenografts. To this aim, we used
immunodeficient mice xenografted with human RKO cells. Nineteen days after
cell injection, palpable tumors were present in all animals, and cohorts of mice
were treated with vehicle or carfilzomib. Figure 6A shows that treatment of
mice with carfilzomib generally elicited a potent growth inhibition of RKO CRC
tumors. Moreover, proteasome inhibitor promoted severe shrinkage in most of
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Proteasome inhibitors are active on BRAF mutant cells
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the individual treated tumors (Fig. 6B). These encouraging results support the
clinical testing of carfilzomib in BRAF mutant metastatic CRC patients.
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Proteasome inhibitors are active on BRAF mutant cells
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DISCUSSION
Establishing pharmacogenomic relationships between genetic aberrations and
targeted therapies is an important goal for researchers and clinicians in the
era of ‘precision medicine’. However, the presence of a single genetic lesion
that is known to be a potential driver of malignant proliferation in a particular
cancer does not always predict a priori response to treatment. Indeed, recent
clinical evidence has indicated that combinations of genetic alterations within
the same tumor can influence drug response (12, 14). Thus, the development
of a model in which mutations can be systematically combined and tested for
drug sensitivity or resistance is of increasing importance.
Several previous studies have attempted to unveil cancer pharmacogenomic
relationships. Isogenic cell models able to effectively recapitulate single
genetic aberrations have been employed extensively to establish binary drug-
genotype associations (20, 30, 31). Yet, limited efforts have been dedicated to
dissect the role of combinations of mutations in determining drug response.
Among these studies, it is worth mentioning the use of isogenic cell lines to
evaluate the influence of KRAS or TP53 status on the sensitivity to specific
anti-cancer therapies in defined genetic backgrounds (32-35).
This report aimed to identify new pharmacogenomic relationships by
screening 43 selected compounds on a panel of isogenic models harboring
multiple cancer associated alterations. In comparison to previous studies, two
major improvements have been implemented. First, we employed epithelial
human cell models that closely recapitulated combinations of cancer
mutations. Indeed, knock-in of nucleotide changes in oncogenes and knock-
down of tumor suppressor genes were coupled to build a genetic ‘matrix’ in
the human breast epithelial cell line HME-1 (15). The advantage of this matrix
is that expression levels of mutant oncoproteins are similar to levels observed
in human tumors, as they are controlled by endogenous genomic elements.
Second, we screened a panel of 43 selected compounds, including a number
of last generation and FDA-approved targeted therapies, to maximize the
translational impact of the screening outcome.
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Proteasome inhibitors are active on BRAF mutant cells
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The ‘pharmarray’ approach that we previously developed (20), was then
applied to analyze the drug screening profiles of the combinatorial HME-1
‘matrix’ (15). By the use of the cell matrix, previous observations that EGFR KI
cells show increased sensitivity to the EGFR kinase inhibitors gefitinib and
erlotinib (20) were extended to novel HER targeted agents such as
vandetanib, canertinib and lapatinib. Consistent with previous studies, this
phenotype was partially rescued by the silencing of the PTEN tumor
suppressor gene, confirming that our model system can recapitulate complex
pharmacogenomic relationships found in lung tumors (12). We envision that
the use of more dedicated methods of analysis of the pharmarray data will
unveil other similar interactions in which the drug-response is impacted by
PTEN or RB1 silencing in specific KI genotypes. Indeed, those relationships
might become evident by systematically analyzing drug responses normalized
versus different genotypes instead of wild-type cells.
However, in the present work, we aimed to show novel pharmacogenomic
relationships that were not significantly affected by the concomitant
inactivation of the tumor suppressor genes analyzed in the matrix. Pharmarray
analysis showed that the BRAF mutant cells were preferentially targeted by
the proteasome inhibitor bortezomib independently from the silencing of PTEN
or RB1.
The genotype-specific activity of bortezomib was corroborated by the use of
an irreversible proteasome inhibitor, carfilzomib, suggesting that this effect
was due to target inhibition and not to peculiar pharmacological properties of
bortezomib. Interestingly, this pharmacogenomic relationship was also
observed in KRAS G13D mutant cells albeit less pronounced than in BRAF
V600E cells. Our results therefore support claims that proteasome inhibitors,
such as MG132 and bortezomib, display synthetic lethality with respect to
KRAS mutations in cancer cells (36).
Selective targeting of BRAF mutant cells by proteasome inhibitors was not
affected by concomitant inactivation of PTEN or RB1 tumor suppressors. This
is different from what was previously reported for BRAF/MEK inhibitors as
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Proteasome inhibitors are active on BRAF mutant cells
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concomitant mutational inactivation of PTEN or RB1 diminished response to
those agents in melanomas harboring BRAF V600E (37). Therefore, targeting
the proteasome may represent a valuable alternative to BRAF or MEK kinase
inhibition for the treatment of BRAF-mutant tumors harboring PTEN or RB1
alterations.
BRAF inhibitors showed poor activity also in BRAF mutated metastatic CRC
(17, 29) and novel treatment strategies are required to improve treatment
options and survival in such patients.
While bortezomib was the first proteasome inhibitor to show antitumor activity
against a variety of hematologic malignancies, it demonstrated poor efficacy
as a single agent in both phase I and II trials on a broad range of solid tumors,
including CRC (38-40). Carfilzomib is the first new generation FDA-approved
proteasome inhibitor. Differently from bortezomib, carfilzomib is an irreversible
inhibitor, characterized by a potent and persistent proteasome inhibition and
greater selectivity for the chymotrypsin-like activity of the proteasome (41). It
showed anti-tumor activity on xenografted cancer cell lines originating from
solid tumors (42). A phase 1 study of carfilzomib has shown that it is well
tolerated with consecutive day dosing (43), and a phase 1b/2 study on
relapsed solid tumors is ongoing [http://www.clinicaltrials.gov].
For the above reasons, we sought to confirm the preferential targeting of
BRAF mutant cells by carfilzomib in cancer models of CRC origin.
Importantly, we demonstrated that carfilzomib preferentially inhibited the
growth of mutant BRAF with respect to the wild-type CRC cell lines,
corroborating the results obtained in the isogenic models. Carfilzomib
exhibited a potent anti-neoplastic activity as single agent also in vivo on the
RKO BRAF-mutant CRC cell line.
The encouraging results from pre-clinical trials and the findings reported in
this work suggest that new generation irreversible proteasome inhibitors may
represent a valuable approach to target CRC cells harboring the BRAF V600E
mutation.
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Proteasome inhibitors are active on BRAF mutant cells
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It should be acknowledged that our screening showed exceptions to the
selective targeting of BRAF mutant CRC cells by carfilzomib. We believe that
the characterization of those outliers is important to understand the basis of
the genotype-specific inhibition by anti-proteasome compounds. This
approach may also help in better defining the subset of patients that most
likely would benefit from anti-proteasome treatments, since there are currently
no predictive biomarkers for this class of agents.
We hypothesized that some of those exceptions may be explained by known
mechanisms of resistance to BRAF inhibitors in BRAF mutant CRC cells. It
was shown that EGFR expression confers primary resistance to BRAF
inhibition in BRAF V600E mutant CRC (29). Nevertheless, EGFR expression
did not correlate with sensitivity to proteasome inhibitors in our cell panel.
Another hypothesis relies on the observation that BRAF mutant CRC samples
are frequently associated to microsatellite instable (MSI) phenotype (44) . As
many BRAF mutant cell lines employed in the present study are MSI,
including the LIM1215 KI BRAF isogenic models, we cannot rule out the
possibility that microsatellite instability contribute together with BRAF V600E
mutation to increase the sensitivity to proteasome inhibition.
To our knowledge, this is the first report to show that proteasome inhibition
could act preferentially on cancer cells with oncogenic BRAF.
Mechanistically, we speculate that BRAF-mutant cells may experience a non-
oncogenic addiction to the proteasome function because the protein
degradation mediated by the ubiquitin-proteasome system is needed to
counterbalance the proteotoxic stress induced by the mutant protein. Indeed,
different oncogenes have been associated to proteotoxic stress responses
(45) and phenomena of non-oncogenic addiction to the proteasome activity
have been shown also for KRAS mutant cells (36, 46). The evidence that –
following proteasome blockade - a higher accumulation rate of ubiquitinated
proteins occurred in mutant cells with respect to the wild type supports our
model. Importantly, in support of our hypothesis, we also showed that the
dependence from proteasome function is dependent upon the persistence of
BRAF V600E activity.
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Proteasome inhibitors are active on BRAF mutant cells
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In conclusion, we have shown that isogenic models in the “matrix” described
in this paper can be exploited for synthetic lethality screenings to identify
drugs that are selectively toxic for cancer cells carrying complex tumor
genotypes. Indeed, this analysis led to the identification of the new, potentially
relevant drug-genotype correlation between BRAF mutation and proteasome
inhibition.
We acknowledge that combinations of multiple drugs are often needed to
maximize the anti-tumor effect and to delay the onset of resistance (47). The
next challenge of personalized medicine will be tailoring the right
combinatorial therapy to the right complex tumor genotype. Indeed,
approaches to perform high-throughput screenings of combinations of
compounds have been published and showed remarkable results also in the
analysis of BRAF mutant melanoma cells (48, 49). Therefore, we envision that
the screening of drug combinations on specific components of the matrix,
such as genotypes harboring BRAF mutation, will represent a valuable
strategy to unveil more effective therapy-genotype correlations.
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FIGURE LEGENDS
Figure 1
HME-1 mutant cells display drug responses resembling those of tumors
carrying equivalent mutations. (A) The effect of erlotinib, canertinib,
vandetanib or lapatinib treatment on cellular proliferation was assessed for
HME-1 isogenic clones carrying the indicated mutations. Drugs were used at
the given concentrations. Cell viability was estimated by determining ATP
content in three replicate wells. Results are normalized to the growth of cells
treated with DMSO and are represented as mean ± SEM of at least three
independent experiments. (B) Multiple concentrations of erlotinib were tested
on HME-1 isogenic clones carrying the indicated mutations. Cell viability was
evaluated by determining ATP content in three replicate wells. Results are
normalized to the growth of cells treated with DMSO and are represented as
mean ± SD of one representative experiment out from three. P values were
determined by Student t test. * P<0.01; ** P<0.001
Figure 2
Drug profiling of isogenic HME-1 cells uncovers bortezomib as a preferential
inhibitor of BRAF/KRAS/PIK3CA mutant cells. Magnification of a drug cluster
from the Pharmarray panel. The cell line genotype is shown on the vertical
axis. Genotypes are defined according to the color code indicated in the
legend. Cells carrying the indicated genetic alterations were clustered using a
hierarchical un-supervised algorithm based on their response profile versus
the whole library; drug names included in the cluster are listed on the
horizontal axis on the top of the panel. For each compound the lowest
concentration used was annotated with the number 1, intermediate
concentration with 2 and the highest with 3. The drug name is followed by the
molecular target on which the compound is reported to act (in brackets). Red-
colored boxes indicate drugs that, at the indicated concentrations,
preferentially inhibited the growth of mutated cells, whilst green boxes show
compounds to which mutated cells were more resistant compared to the wild
type counterpart. Black boxes indicate no significant difference in response
between mutant and parental cells, whilst grey boxes indicate experiments not
performed.
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Proteasome inhibitors are active on BRAF mutant cells
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Figure 3
HME-1 clones harboring the BRAF V600E mutation showed increased
sensitivity to proteasome inhibitors. (A) Effect of the Proteasome inhibitors
bortezomib or carfilzomib on isogenic HME-1 cells wild type, BRAF or EGFR
mutated. Cell viability was estimated by determining ATP content in three
replicate wells. Results are normalized to growth of cells treated with DMSO
and are represented as mean ± SD of at least three independent experiments.
(B) Chemical structures, molecular formulas and molecular weights of
proteasome inhibitors bortezomib and carfilzomib. (C) Biochemical effects
induced by treatment with increasing concentrations of Bortezomib were
tested by Western Blot on HME-1 wild type or BRAF KI cell lines. Ubiquitin
and P21 accumulation were measured by antibodies recognizing the
respective proteins and changes in the levels of both the full-length and the
cleaved form of PARP were assessed by an anti-PARP antibody. Antibody
against actin was used as a loading control. Different nanomolar
concentrations of the drug are reported in the upper panel of the figure;
densitometric quantification of the ubiquitin smears is reported above the
lanes. NT = not treated controls. (D) Basal chymotrypsin-like proteasome
activity is higher in HME-1 KI BRAF as compared to HME-1 wild type cells,
while titration with bortezomib reduced the activity to similar levels in the
different cell lines. 24 h after seeding, cells were treated with bortezomib for 3
h before exposure to luminogenic substrate for 15 min. Data are represented
as mean ± SD. One KI clone is represented from two independently tested.
NT = not treated controls. P value was determined by Student t test. ***
P<0.001 versus control.
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Proteasome inhibitors are active on BRAF mutant cells
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Figure 4
BRAF mutant CRC lines are highly sensitive to proteasome inhibitors. Effect
of the proteasome inhibitors bortezomib 40nM (A) or carfilzomib 800nM (B) on
wild-type LIM1215 CRC cells or on two independent BRAF KI clones (called
KI BRAF 1 and KI BRAF 2). Cell viability was estimated by determining ATP
content in three replicate wells. Results are normalized to the growth of cells
treated with DMSO and are represented as mean ± SEM of at least three
independent experiments performed in triplicate. P values were determined by
Student’s t test. * P<0.05; ** P<0.01 versus control. (C) Carfilzomib was tested
on a panel of colorectal cancer cell lines wild type for BRAF and KRAS (left
side, black columns) or harboring the BRAF V600E mutation (right side, white
columns). A single concentration of the drug was assayed on all cell lines
(800nM). Cell viability was estimated by determining ATP content in three
replicate wells. Results are normalized to growth of cells treated with DMSO
and are represented as mean ± SD of at least three independent experiments.
* P<0.05 T test between the viability of the two groups of cell lines. (D) The
expression of RB1, PTEN or EGFR proteins was tested on the panel of
colorectal cancer cell lines by western blot. Protein lysates were loaded in the
same order as indicated above and incubated with anti-RB1 anti-PTEN or
anti-EGFR antibodies. Actin was used as a loading control.
Figure 5
BRAF signaling determines vulnerability to proteasome inhibitors in BRAF
mutant CRC cells. The effect of multiple concentrations of carfilzomib and
PLX4720, alone or in combination, was assessed on the BRAF-mutant cell
lines LS411N (A-B) and SNUC-5 (C-D). Cell viability was determined by
calculation of ATP content in triplicate in LS411N (A) or in SNUC-5 (C).
Results were normalized to the growth of cells treated with DMSO and are
represented as mean ± SD of a representative experiment from three. By the
method of Poch et al. (23), the observed effect of the combination at each
concentration is lower than the expected effect (independent action) for
LS411N (B) and SNUC-5 (D) cell lines.
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Proteasome inhibitors are active on BRAF mutant cells
27
Figure 6
Carfilzomib suppresses the growth of BRAF mutant RKO xenografts. (A)
Following tumor establishment (200–250mm3), mice were treated with vehicle
or carfilzomib i.v. at 4mg/kg. Tumor volumes are shown as mean ±SEM (n=6
mice per group). The arrow indicates the time at which treatment was started.
(B) Waterfall plot showing the percent change in volume for the individual
tumors in each arm following 30 days’ vehicle or carfilzomib treatment. Tumor
volumes were normalized individually to their volume at treatment day 1.
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Figure 1
AA
80
100
120
ntro
l) ******
******
*****
******
20
40
60
80
Viab
ility
(%
Con scramble
EGFR
EGFR+PTEN
BRAF
0Erlotinib
1 μMCanertinib 0.12 μM
Vandetanib 1.2 μM
Lapatinib 1 μM
B
100
120 HME-1 WTHME-1 EGFR del746-750l)
20
40
60
80
100 G de 6 50HME-1 EGFR del746-750 shPTEN
Via
bilit
y (%
Con
trol
10-8 10-7 10-6 10-50
20
Erlotinib [M]
V
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Figure 2Scramble shRNA PTEN shRNA RB1shRNA
HME-1 parentalKI BRAF V600E KI EGFR del746-750 KI KRAS G13D KI PIK3CA E545KKI PIK3CA H1047R
EGFR
-1/2/
PDGF
R/c-K
itD
AC)
asom
e)as
ome)
F-1R
)F-
1R)
1&3)
AC)
asom
e)1)
Sora
fenib
(RAF
/VE
Valp
roic
Aci
d (H
D
17-A
AG (H
SP90
)
Borte
zomi
b (pr
otea
Borte
zomi
b (pr
otea
NVP-
AEW
541 (
IGF
NVP-
AEW
541 (
IGF
GW84
3682
X (P
LKMe
tform
in (A
MPK)
Valpr
oic A
cid (H
DABo
rtezo
mib (
prote
aOS
U-03
012 (
PDK-
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Figure 3
A
80
100
120 HME-1 WT SCRA
HME-1 KI BRAF 2HME-1 KI BRAF 1HME-1 KI EGFR
Co
ntro
l)80
100
120 HME-1 WT SCRA
HME 1 KI BRAF 2HME-1 KI BRAF 1HME-1 KI EGFR
Co
ntro
l)
10 -9.0 10 -8.5 10-8.0 10-7.50
20
40
60HME 1 KI BRAF 2
Bortezomib [M]
Via
bili
ty (
% C
10 -8.0 10 -7.5 10 -7.0 10 -6.5 10 -6.00
20
40
60HME-1 KI BRAF 2
Carfilzomib [M]
Via
bili
ty (
% C
B
HME-1 WT HME-1 KI BRAFV600EC
CarfilzomibMolecular Formula: C40H57N5O7
Molecular Weight: 719.91
BortezomibMolecular Formula: C19H25BN4O4
Molecular Weight: 384.24
NT 8 164
HME 1 WT HME 1 KI BRAF
Anti-UBIQUITIN
NT 8 164+ Bortezomib (nM)
C
1 1.3 2.4 3.4 1.2 2.2 3.1 3.6
Anti-P21
Anti-PARPfull-length
cleaved
Anti-ACTIN
150000
200000
250000
ctiv
ity
(RL
U)
HME-1 WT
HME-1 KI BRAF
***
D
0
50000
100000
NT 4nM Bortezomib 8nM Bortezomib
Pro
tea
som
e A
c
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Figure 4
A BB t ib Carfil omib
30
40
50
60
(% C
ontr
ol)
Bortezomib
20
30
40
50
y (%
Con
trol
)
Carfilzomib
***
****
0
10
20
Viab
ility
(
0
10
Viab
ility
120 BRAF V600EWT
p<0.05C
60
80
100
Con
trol
)
BRAF V600EWT
0
20
40
60
Viab
ility
(%
0
OU
MS
23
CO
LO20
1
OX
CO
1
SW
1417
LIM
2405
LIM
2537
KM
20
HD
C13
5
RK
O
CA
CO
2
CO
LO32
0
NC
I H63
0
NC
I H71
6
CA
R1
DIF
I
HuT
u80
HC
A7
LS 4
11N
SN
UC
5
VA
CO
432
Rb1
D
PTENEGFRActin
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Figure 5LS411N (BRAF V600E) LS411N (BRAF V600E)A B
0.0625 0.125 0.25 0.5 1 2140
PLX4720 concentration (μM)
140
PLX4720 concentration (μM)0.0625 0.125 0.25 0.5 1 2
0
20
40
60
80
100
120
140PLX4720
PLX4720 + CarfilzomibCarfilzomib
18 75 37 5 75 150 300 600
Viab
ility
(% C
ontro
l)
18 75 37 5 75 150 300 6000
20
40
60
80
100
120
140
Independent actionCombination
Viab
ility
(% C
ontro
l)
SNUC-5 (BRAF V600E) SNUC-5 (BRAF V600E)C D
18.75 37.5 75 150 300 600
Carfilzomib concentration (μM)(nM)18.75 37.5 75 150 300 600
Carfilzomib concentration (μM)(nM)
0.0625 0.125 0.25 0.5 1 2140
PLX4720 concentration (μM)
140
PLX4720 concentration (μM)0.0625 0.125 0.25 0.5 1 2
0
20
40
60
80
100
120
140PLX4720
PLX4720 + CarfilzomibCarfilzomib
Viab
ility
(% C
ontro
l)
0
20
40
60
80
100
120
140
Independent actionCombination
Viab
ility
(% C
ontro
l)
18.75 37.5 75 150 300 600
Carfilzomib concentration (μM)(nM)18.75 37.5 75 150 300 600
Carfilzomib concentration (μM)(nM)
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Figure 6
A 1400
EM
)RKO V hi l
A
800
1000
1200m
m3
(Mea
n ±
SE RKO Vehicle
RKO Carfilzomib
0
200
400
600
umor
Vol
ume
m
00 10 20 30 40 50 60
Tu
Days
B700
m Carfilzomib
300
400
500
600
mor
Vol
ume
fro
mel
ine
CarfilzomibVehicle
0
100
200
300
% C
hang
e T
um
base
-100
0%
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Published OnlineFirst October 9, 2013.Mol Cancer Ther Davide Zecchin, Valentina Boscaro, Enzo Medico, et al. inhibitorsBRAF V600E is a determinant of sensitivity to proteasome
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